Covid Report for Family

Background

Notes and format last updated Apr 16, 2020

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	16,932
2	New Jersey	14,848
3	Massachusetts	10,449
4	Rhode Island	9,633
5	Connecticut	8,693
6	District of Columbia	7,737
7	Louisiana	6,539
8	Delaware	5,933
9	Illinois	5,379
10	Maryland	4,674
11	Michigan	4,510
12	Pennsylvania	4,295
13	Nebraska	3,505
14	Indiana	3,310
15	Iowa	3,297
16	South Dakota	3,141
17	Colorado	3,077
18	Mississippi	2,830
19	Georgia	2,799
20	Virginia	2,373
21	Washington	2,194
22	New Mexico	2,046
23	Kansas	2,023
24	Tennessee	2,020
25	New Hampshire	2,015
26	Nevada	1,874
27	Ohio	1,845
28	Alabama	1,772
29	Florida	1,768
30	Utah	1,748
31	North Dakota	1,736
32	California	1,538
33	Wisconsin	1,528
34	Minnesota	1,521
35	Missouri	1,493
36	Vermont	1,455
37	South Carolina	1,347
38	Arizona	1,333
39	Kentucky	1,330
40	Texas	1,222
41	North Carolina	1,218
42	Idaho	1,207
43	Arkansas	1,196
44	Wyoming	1,090
45	Oklahoma	1,061
46	Maine	932
47	West Virginia	711
48	Oregon	691
49	Puerto Rico	616
50	Alaska	505
51	Hawaii	435
52	Montana	426

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Rhode Island	229
2	New York	222
3	District of Columbia	210
4	Delaware	195
5	New Jersey	193
6	Massachusetts	190
7	Nebraska	188
8	Illinois	175
9	Connecticut	159
10	Maryland	154
11	Iowa	130
12	Indiana	116
13	Minnesota	113
14	Wyoming	112
15	Mississippi	97
16	Kansas	84
17	Louisiana	75
18	Pennsylvania	75
19	New Mexico	70
20	Colorado	69
21	Georgia	66
22	Virginia	61
23	North Dakota	57
24	South Dakota	56
25	Alabama	54
26	Kentucky	54
27	New Hampshire	54
28	Wisconsin	53
29	Washington	49
30	Arizona	48
31	California	48
32	Idaho	47
33	Ohio	47
34	Utah	44
35	Michigan	43
36	Tennessee	42
37	Missouri	38
38	Texas	36
39	North Carolina	35
40	Nevada	32
41	Florida	29
42	South Carolina	20
43	Arkansas	19
44	Oklahoma	19
45	Oregon	18
46	Maine	17
47	Puerto Rico	16
48	West Virginia	15
49	Vermont	5
50	Alaska	1
51	Hawaii	1
52	Montana	0

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New York	1,334
2	New Jersey	962
3	Connecticut	762
4	Massachusetts	641
5	Louisiana	450
6	Michigan	425
7	District of Columbia	392
8	Rhode Island	349
9	Pennsylvania	262
10	Maryland	238
11	Illinois	234
12	Indiana	204
13	Delaware	198
14	Colorado	159
15	Mississippi	125
16	Georgia	123
17	Washington	115
18	Ohio	104
19	Nevada	92
20	Minnesota	85
21	Vermont	84
22	Virginia	83
23	New Hampshire	81
24	New Mexico	80
25	Florida	71
26	Alabama	69
27	Iowa	69
28	Missouri	69
29	Kentucky	64
30	Oklahoma	63
31	California	62
32	Wisconsin	62
33	South Carolina	59
34	Arizona	58
35	Kansas	55
36	North Carolina	47
37	Maine	46
38	Nebraska	44
39	North Dakota	40
40	Idaho	37
41	Tennessee	36
42	Texas	33
43	South Dakota	32
44	Puerto Rico	30
45	Arkansas	28
46	West Virginia	28
47	Oregon	27
48	Utah	18
49	Montana	14
50	Hawaii	12
51	Wyoming	12
52	Alaska	10

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	New York	115
2	Connecticut	26
3	New Jersey	25
4	Massachusetts	20
5	Rhode Island	15
6	Maryland	14
7	Pennsylvania	13
8	District of Columbia	12
9	Indiana	12
10	Illinois	9
11	Louisiana	8
12	Mississippi	7
13	Michigan	6
14	New Hampshire	6
15	Delaware	5
16	Ohio	5
17	Colorado	4
18	Georgia	4
19	Puerto Rico	4
20	Alabama	3
21	Iowa	3
22	Minnesota	3
23	South Dakota	3
24	Arizona	2
25	California	2
26	Florida	2
27	Kansas	2
28	Kentucky	2
29	Missouri	2
30	Nevada	2
31	New Mexico	2
32	North Dakota	2
33	Virginia	2
34	Arkansas	1
35	Maine	1
36	Nebraska	1
37	North Carolina	1
38	Oklahoma	1
39	South Carolina	1
40	Tennessee	1
41	Texas	1
42	Washington	1
43	Wisconsin	1
44	Alaska	0
45	Hawaii	0
46	Idaho	0
47	Montana	0
48	Oregon	0
49	Utah	0
50	Vermont	0
51	West Virginia	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Trousdale	Tennessee	120,082	1	99
Lincoln	Arkansas	67,798	2	99
Dakota	Nebraska	50,634	3	99
Nobles	Minnesota	50,025	4	99
Bledsoe	Tennessee	39,896	5	99
Davidson	Tennessee	4,820	222	92
Richland	South Carolina	2,439	547	82
Pierce	Washington	1,765	752	76
Orange	California	958	1219	61
York	South Carolina	790	1414	54

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Randolph	Georgia	2,951	1	99
Terrell	Georgia	2,462	2	99
Early	Georgia	2,453	3	99
Nassau	New York	1,713	4	99
Essex	New Jersey	1,688	5	99
Richland	South Carolina	118	478	84
Pierce	Washington	60	790	74
Davidson	Tennessee	48	908	71
Orange	California	20	1271	59
York	South Carolina	18	1312	58

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.